• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.91-96
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• 2012

Ad-hoc networks can be used various environment, which it is difficult to construct infrastructures, such as shadowing areas, disaster areas, war area, and so on. In order to support to considerable and various wireless services, more spectrum resources are needed. However, efficient utilization of the frequency resource is difficult because of spectrum scarcity and the conventional frequency regulation. Ad-hoc networks employing cognitive radio (CR) system that guarantee high spectrum utilization provide effective way to increase the network capacity. In CR based wireless ad-hoc networks, cluster-head decides the existence of primary user using sensing information of primary user from each ad-hoc device. However, it is still defective research to decide cluster head among the a lot of ad-hoc devices. So, in this paper, we show the decision method of cluster head in CR based wireless and detection probabilities of primary user based on decision method of cluster head.

• Journal of KIISE
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• v.43 no.1
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• pp.61-70
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• 2016

In recent years, there has been a need for techniques for large-scale ontology inference in order to infer new knowledge from existing knowledge at a high speed, and for a diversity of semantic services. With the recent advances in distributed computing, developments of ontology inference engines have mostly been studied based on Hadoop or Spark frameworks on large clusters. Parallel programming techniques using GPGPU, which utilizes many cores when compared with CPU, is also used for ontology inference. In this paper, by combining the advantages of both techniques, we propose a new method for reasoning large RDFS ontology data using a Spark in-memory framework and inferencing distributed data at a high speed using GPGPU. Using GPGPU, ontology reasoning over high-capacity data can be performed as a low cost with higher efficiency over conventional inference methods. In addition, we show that GPGPU can reduce the data workload on each node through the Spark cluster. In order to evaluate our approach, we used LUBM ranging from 10 to 120. Our experimental results showed that our proposed reasoning engine performs 7 times faster than a conventional approach which uses a Spark in-memory inference engine.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.6
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• pp.635-645
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• 2003

One of very important features that are necessarily supported by clustered parallel computer systems is a single I/O system image in which users can access both the local and remote I/O resources transparently. In this paper, we propose an efficient disk sharing technique supporting a single disk I/O system image architecture. The design separates the I/O subsystem of a cluster into the file system and a set of virtual hard disk drivers. The virtual hard disk driver deals with a hard disk in the remote node as a local hard disk. All services provided by it are performed in the device driver level without any modification of file systems. Users can, therefore, access all the disks in the cluster regardless of their locations. Our virtual hard disk driver is implemented under the linux, and also tested in a linux cluster system. We find by experiments that it can successfully support a single disk I/O space, and at the same time it shows better performance than NFS. We are sure that this paper can be a guideline for single I/O space of other devices to be easily constructed.

• Annual Conference of KIPS
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• 2004.05a
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• pp.199-202
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• 2004

레거시 시스템을 위한 기존의 도메인 분석의 문제점을 해결하기 위하여 동적인 모델링인 확장된 워크플로우 메커니즘을 기반으로 하는 도메인 분석 방법을 제안하고자 한다. 이 도메인 분석을 통해 공통/비공통의 프로세스 컴포넌트 식별 및 공통 프로세스 컴포넌트들의 클러스터를 추출하고 마지막 단계에서 UML 기법으로 컴포넌트 내의 객체를 추출할 수 있다. 또한 제안한 컴포넌트 가중치 측정 매트릭스에 적용해 사용 빈도수가 많거나 중요한 컴포넌트 및 컴포넌트 클러스터를 찾는 방법을 제시하고자 한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.109-112
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• 2020

사람 재인식을 수행하기 위해서 많은 연구들이 진행되어 좋은 결과들을 보였다 그러나 이 결과들은 라벨이 있는 도메인에서의 지도 학습으로 얻은 결과들이었다. 라벨이 없는 도메인에서의 사람 재인식의 성능은 아직 많이 부족한 상태이다. 사람 재인식을 수행하고자 하는 목표 도메인에 반해 주어진 소스 도메인에서는 라벨이 풍부하다. 지금까지의 논문에서는 소스 도메인에서의 사람 이미지를 목표 도메인의 이미지처럼 만들어서 소스 도메인에서 높은 성능을 보이는 사람 재인식기를 목표 도메인에서도 잘 동작하도록 학습하는 방법들이 주를 이루었다. 하지만 이 방법에서는 소스 도메인의 사람 이미지를 목표 도메인의 이미지와 비슷하게 만들기만하고 사람의 신원에 대한 일관성을 유지시키지는 못하였다. 본 논문에서는 비지도 도메인 적응 사람 재인식을 수행하기 위해 클러스터 일관성(cluster consistency)을 유지하는 기법을 제안한다. 제안한 방법은 사람의 신원에 대한 일관성을 유지시켜서 사람 재인식의 성능을 높인다.

• Annual Conference of KIPS
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• 2007.05a
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• pp.1435-1438
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• 2007

여러 대의 컴퓨터를 하나의 네트워크로 연결한 클러스터 시스템은 일반적으로 웹 부하 분배, VOD 스트리밍 서비스 그리고 슈퍼컴퓨터, 혹은 메인프레임 급의 성능이 필요한 거대한 작업을 위해서 사용된다. 본 논문에서는 클러스터 기법을 사용하여 안정적이고 높은 성능을 보장하는 백업 시스템을 설계 및 구현하는 내용에 대해서 기술하고 있다. 기존의 데이터 백업 시스템과 비교하여 저가격에 높은 효율성을 제공할 수 있는 장점을 제공하며, 안정성 및 신뢰성을 높이 향상시킬 수 있음을 보이고 있다.

• Journal of IKEEE
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• v.13 no.2
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• pp.167-174
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• 2009

Music evokes human emotions or creates music moods through various low-level musical features. Typical music clip consists of one or more moods and this can be used as an important criteria for determining the similarity between music clips. In this paper, we propose a new music retrieval scheme based on the mood change patterns of music clips. For this, we first divide music clips into segments based on low level musical features. Then, we apply K-means clustering algorithm for grouping them into clusters with similar features. By assigning a unique mood symbol for each cluster, we can represent each music clip by a sequence of mood symbols. Finally, to estimate the similarity of music clips, we measure the similarity of their musical mood sequence using the Longest Common Subsequence (LCS) algorithm. To evaluate the performance of our scheme, we carried out various experiments and measured the user evaluation. We report some of the results.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.5
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• pp.827-834
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• 2024

LEACH, a layer-based routing protocol used in wireless sensor networks, sends fused data from the cluster head to the sink node in a single hop, so as the network size increases, the distance to the sink node increases significantly, which increases energy consumption. In addition, existing multi-hop transmission studies to solve this problem have problems with reverse transmission in the process of finding the next node to be transmitted and passing through this node. In this paper, we propose a multi-hop routing technique that selects a relay node based on the distance to the sink node and transmits it to a relay node via general nodes located in a straight line between the relay node and each cluster head. By reducing the transmission distance between nodes and minimizing reverse transmission occurring in the process through adjacent nodes, it was confirmed that the network life was extended compared to the previously proposed LEACH and EEACP protocols.

• Convergence Security Journal
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• v.16 no.2
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• pp.3-9
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• 2016

Recently, a lot of researches have been done to increase the life span of network using the energy efficient sensor node in WSN. In the WSN environment, we must use limited amount of energy and hardware. Therefore, it is necessary to design energy efficient communication protocol and use limited resources. Cluster based routing method such as LEACH and HEED get the energy efficient routing using data communication between cluster head and related member nodes. In this paper, we propose an energy efficient routing algorithm as well as performance result using simulation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.942-949
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• 2016

Efficient routing protocols designed for Wireless Sensor Networks (WSN) can be extended and applied to Internet of Things (IoT) data routing, as IoT can be considered to be an extension from WSN. When the size of the data in IoT is often bigger than in conventional WSNs, existing cluster routing protocol such as LEACH may cause high data loss rate due to its incomplete load balancing. We present an enhanced LEACH-based protocol which can minimize the data loss which is an important performance measure in IoT. In our proposed protocol, the base station estimates the location of nodes by the trilateration technique to make sure optimal number of cluster heads and members in a deterministic manner. We evaluate our proposed protocol via computer simulations in terms of data loss rate and average network lifetime.